Method and network node for generating and selecting a codebook in a MIMO communication network

ABSTRACT

A method in a network node for Multiple Input Multiple Output (MIMO) is provided. The method comprises: obtaining a precoding matrix indicator (PMI) for a first codebook for use in a Single User Multiple Input Multiple Output (SU-MIMO) transmission; determining a precoding matrix for a second codebook, based on the obtained precoding matrix indicator; and selecting the determined precoding matrix for the second codebook in response to determining that an User Equipment (UE) is scheduled for a Multi-User (MU)-MIMO transmission. A network node for performing this method is also provided.

TECHNICAL FIELD

The present description generally relates to generating and selecting acodebook for precoding data in a communication network.

BACKGROUND

Active antenna system (AAS) is one of the key technologies adopted by 4GLong Term Evolution (LTE) and 5G New Radio (NR) to enhance the wirelessnetwork performance and capacity by using Full Dimension Multiple InputMultiple Output (FD-MIMO) and massive MIMO. A typical AAS systemconsists of two-dimensional antenna elements array with M rows, Ncolumns and K polarizations (K=2 in case of cross-polarization) as shownin FIG. 1.

A typical application of AAS is to perform DownLink Multi-User MIMO (DLMU-MIMO) which allows the frequency resources to be shared by multipleUser Equipment (UEs) with co-scheduling transmissions at the same time.As a result, the co-scheduled UEs suffer from the co-channelinterference, as can be seen in FIG. 2, which is one of the biggestchallenges for DL MU-MIMO.

In order to achieve a good MU-MIMO performance, one of the approachesconsists of having a codebook for the DL MU-MIMO, which tries to pairUEs with good spatial separation together. For example, the users thatare co-scheduled with the same frequency resource should have goodspatial separation from each other. Such a codebook may have a set ofprecoding matrices which are pre-defined. The optimum beam index orprecoding matrix indicator (PMI) is reported by the UE with the ChannelState information-Reference Signal (CSI-RS) report to the network node,such as an eNB/gNB. The optimum beam index can be also estimated at theeNB/gNB side by using UpLink (UL) reference signals (e.g. SRS or DMRS).At the eNB/gNB side, an UE pairing algorithm is used to find the UEswhich are well separated from each other and thus can be co-scheduledtogether with minimized co-channel interference.

In 3GPP Release 13 (Rel-13), a two-dimensional (2D) Discrete FourierTransform (DFT) codebook is proposed in [1][2] for non-precoded CSI-RS(“CLASS A”). The precoding matrix W is further described as a two-stageprecoding structure as follows:W=W ₁ W ₂

where the matrix W₁ consists of a group of 2D grid-of-beams (GoB)denoted as:

$\begin{matrix}{W_{1} = \begin{bmatrix}{w_{h} \otimes w_{v}} & 0 \\0 & {w_{h} \otimes w_{v}}\end{bmatrix}} & (1)\end{matrix}$

Where w_(h) and w_(v) are precoding matrices selected from anover-sampled DFT matrix for the horizontal direction and verticaldirection, and they are expressed as:

$w_{v} = {\frac{1}{\sqrt{M}}\left\lbrack {1,e^{\frac{j2\pi v}{MO_{1}}},{\ldots\mspace{14mu} e^{\frac{j2\pi mv}{MO_{1}}}},{\ldots\mspace{14mu} e^{\frac{j2{\pi{({M - 1})}}v}{MO_{1}}}}} \right\rbrack}^{T}$$w_{h} = {\frac{1}{\sqrt{N}}\left\lbrack {1,e^{\frac{j2\pi h}{NO_{2}}},{\ldots\mspace{14mu} e^{\frac{j2\pi nv}{NO_{2}}}},{\ldots\mspace{14mu} e^{\frac{j2{\pi{({N - 1})}}h}{NO_{2}}}}} \right\rbrack}^{T}$

Where O₁, O₂ are the over-sampling rates in the vertical and horizontaldirections respectively, M refers to the number of rows of antennaelements and N refers to the number of columns of antenna elements in anAAS. For example, for a 2D AAS, as shown in FIG. 1, the horizontaldirection refers to the antenna elements of each row, which form thebeams in the direction parallel to the ground. The vertical directionrefers to the antenna elements of each column, which form the beams inthe direction vertical to the ground.

The matrix W₂ is used for beam selection within W₁ and co-phasingbetween two polarizations.

One of the problems of the DFT-based codebook for DL MU-MIMO is thestrong sidelobe interference experienced by the co-scheduled UEs asshown in FIG. 3.

FIG. 3 shows the beam radiation pattern of a DFT-based precoding matrix(at index 0) with 8 Transmit (Tx) linear antenna array in a Line ofSight (LOS) channel model. It can be seen that there are multiplesidelobes leaked out of the main-lobe. These sidelobe leakages aredominant interference to other co-scheduled UEs located at around thesidelobe directions or positions, especially in Non-LOS (NLOS) scenariowhere there is an angle of spread of the multi-paths. Some sub-pathswould unavoidably go through the sidelobe directions. In this case, thesidelobe interference could be the bottleneck of Signal to Interferenceplus Noise Ratio (SINR) for UEs who have a good Single User (SU)-MIMOchannel quality. For instance, one UE, that is located at the directionof 20° from boresight (e.g. a direction that points to the middle of thecell) and has 30 dB SU-MIMO SINR, is able to achieve a peak throughputfor a SU-MIMO transmission with 64QAM. Unfortunately, with MU-MIMO, theUE will suffer a 12.8 dB sidelobe interference from a co-scheduled UE inboresight. Then, the UE's effective SINR in MU-MIMO would be limited to12.8 dB, which would make it impossible for the UE to reach the SU-MIMOpeak throughput. As it can be seen, the MU-MIMO gain is degradedsignificantly by the sidelobe interference.

For DL MU-MIMO transmissions, the total transmit power is limited. Thegain of MU-MIMO is mainly given by the UEs which have a good SINR, andthe power can be split with other UEs. However, with the DFT codebook,the split power causes strong co-channel interference. Thus, theperformance is limited by co-channel interference caused by strongsidelobe leakage. As such, the gain can be degraded significantly, oreven become negative.

SUMMARY

According to one aspect, there is provided a method in a network node.The method comprises: obtaining a precoding matrix indicator (PMI) for afirst codebook for use in a Single User Multiple Input Multiple Output(SU-MIMO) transmission; determining a precoding matrix for a secondcodebook, based on the obtained precoding matrix indicator; andselecting the determined precoding matrix for the second codebook inresponse to determining that an User Equipment (UE) is scheduled for aMulti-User (MU)-MIMO transmission.

In some embodiments, determining the precoding matrix for the secondcodebook may comprise applying a reshaping matrix to a precoding matrixthat corresponds to the obtained PMI in the first codebook.

In some embodiments, the second codebook can be generated based on thefirst codebook by using a reshaping matrix.

In some embodiments, the reshaping matrix can comprise a matrix formedwith precoding matrices from the first codebook, to which nullingprecoding weights are applied, so that sidelobe leakage in the peakdirections of the sidelobes of the precoding matrices are nulled.

In some embodiments, the reshaping matrix may comprise a matrix formedby applying a tapered window to the first codebook.

In some embodiments, the tapered window is generated using one of aChebyshev window and Taylor window.

In some embodiments, the second codebook may have a one to one mappingwith the first codebook.

In some embodiments, the second codebook may have a lower sidelobeleakage compared to sidelobe leakage of the first codebook in selectedsidelobe directions.

In some embodiments, a two-dimension (2D) codebook may be generatedbased on the second codebook. For example, the 2D codebook may compriseprecoding matrices for a horizontal direction selected from the secondcodebook and precoding matrices for a vertical direction selected fromthe second codebook.

In some embodiments, the 2D codebook may be generated based on thesecond codebook and the first codebook. For example, the 2D codebook maycomprise precoding matrices for a horizontal direction selected from thesecond codebook and precoding matrices for a vertical direction selectedfrom the first codebook. As another example, the 2D codebook maycomprise precoding matrices for a horizontal direction selected from thefirst codebook and precoding matrices for a vertical direction selectedfrom the second codebook.

According to another aspect, there is provided a network node,comprising a network interface and a processing circuitry connectedthereto. The processing circuitry is configured to: obtain a precodingmatrix indicator (PMI) for a first codebook for use in a Single UserMultiple Input Multiple Output (SU-MIMO) transmission; determine aprecoding matrix for a second codebook, based on the obtained precodingmatrix indicator; and select the determined precoding matrix for thesecond codebook in response to determining that an User Equipment (UE)is scheduled for a Multi-User (MU)-MIMO transmission. The processingcircuitry may comprise a processor and a memory connected thereto, thememory containing instructions that, when executed, cause the processorto perform the method and the embodiments as described above withrespect to the first aspect.

Some embodiments of this disclosure may minimize the co-channelinterference from co-scheduled UEs for codebook-based DL MU-MIMOsystems. For example, a new codebook is generated, which is calculatedwith indexes aligned with the regular DFT codebook for SU-MIMO. The newcodebook is easier to be implemented and integrated with SU-MIMOsystems.

The proposed new codebook has a wider window of angle with near-to-zerosidelobe leakage to handle the multipath angle spread, which allows thecodebook-based DL MU-MIMO to be feasible in NLOS scenarios.

The proposed new codebook can also be used by the eNB/gNB for CSI-RSprecoding, sector virtualization and cell shaping to further minimizethe inter-beam, inter-sector and inter-cell interference.

The new codebook can be also used by the UE for CSI estimation.

This summary is not an extensive overview of all contemplatedembodiments, and is not intended to identify key or critical aspects orfeatures of any or all embodiments or to delineate the scope of any orall embodiments. In that sense, other aspects and features will becomeapparent to those ordinarily skilled in the art upon review of thefollowing description of specific embodiments in conjunction with theaccompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments will be described in more detail with reference tothe following figures, in which:

FIG. 1 illustrates a schematic diagram of a two-dimension antennaelement array.

FIG. 2 is a schematic diagram of an example of co-channel interferencein DL MU-MIMO transmissions between UEs.

FIG. 3 illustrates an example of sidelobe interference of a DFTcodebook.

FIG. 4 is a schematic diagram of a communication network, according toan embodiment.

FIG. 5 illustrates an example of a radiation pattern of a codebook withreduced sidelobe leakage with 8 Transmit antennas, according to anembodiment.

FIG. 6 illustrates an example of a radiation pattern of a codebook withreduced sidelobe leakage with 16 Transmit antennas, according to anembodiment.

FIG. 7 illustrates a signaling diagram between a UE and a network node,according to an embodiment.

FIG. 8 is a flow chart of a method in a network node, in accordance withsome embodiments.

FIG. 9 is a block diagram of a wireless device in accordance with someembodiments.

FIG. 10 is a block diagram of a network node in accordance with someembodiments.

FIG. 11 is another block diagram of a network node in accordance withsome embodiments.

FIG. 12 is a virtualized environment for a network node, in accordancewith some embodiments.

DETAILED DESCRIPTION

The embodiments set forth below represent information to enable thoseskilled in the art to practice the embodiments. Upon reading thefollowing description in light of the accompanying figures, thoseskilled in the art will understand the concepts of the description andwill recognize applications of these concepts not particularly addressedherein. It should be understood that these concepts and applicationsfall within the scope of the description.

In the following description, numerous specific details are set forth.However, it is understood that embodiments may be practiced withoutthese specific details. In other instances, well-known circuits,structures, and techniques have not been shown in detail in order not toobscure the understanding of the description. Those of ordinary skill inthe art, with the included description, will be able to implementappropriate functionality without undue experimentation.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to implement such feature, structure, orcharacteristic in connection with other embodiments whether or notexplicitly described.

As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises,”“comprising,” “includes,” and/or “including” when used herein, specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

In the specification, the terms “coupled” and “connected,” along withtheir derivatives, may be used. It should be understood that these termsare not intended as synonyms for each other. “Coupled” is used toindicate that two or more elements, which may or may not be in directphysical or electrical contact with each other, cooperate or interactwith each other. “Connected” is used to indicate the establishment ofcommunication between two or more elements that are coupled with eachother.

FIG. 4 illustrates an example of a wireless network or communicationnetwork 400 that may be used for wireless communications. Wirelessnetwork 400 includes wireless devices 410 and a plurality of radioaccess nodes or network nodes 420 (e.g., eNBs, gNBs, etc.) connected toone or more core network nodes 440 via an interconnecting network 430.The network 400 may use any suitable deployment scenarios, such as anon-centralized, co-sited, centralized, or shared deployment scenario.Wireless devices 410 within a coverage area may each be capable ofcommunicating directly with radio access nodes 420 over a wirelessinterface. In certain embodiments, wireless devices 410 may also becapable of communicating with each other via device-to-device (D2D)communication. In certain embodiments, radio access nodes 420 may alsobe capable of communicating with each other, e.g. via an interface (e.g.X2 in LTE or other suitable interface).

As an example, wireless device 410 may communicate with radio accessnode 420 over a wireless interface. That is, wireless device 410 maytransmit wireless signals and/or receive wireless signals from radioaccess node 420. The wireless signals may contain voice traffic, datatraffic, control signals, and/or any other suitable information. In someembodiments, an area of wireless signal coverage associated with a radioaccess node 420 may be referred to as a cell.

In some embodiments, wireless device 410 may be interchangeably referredto by the non-limiting term user equipment (UE). Wireless device 410 canbe any type of wireless device capable of communicating with networknode or another UE over radio signals. The UE may also be radiocommunication device, target device, device to device (D2D) UE, machinetype UE or UE capable of machine to machine communication (M2M), asensor equipped with UE, iPAD, Tablet, mobile terminals, smart phone,laptop embedded equipped (LEE), laptop mounted equipment (LME), USBdongles, Customer Premises Equipment (CPE), etc. Example embodiments ofa wireless device 410 are described in more detail below with respect toFIG. 9. The wireless device 410 may have multiple antennas, for example.

In some embodiments, the generic terminology “network node” is used. A“network node” refers to equipment capable, configured, arranged and/oroperable to communicate directly or indirectly with a wireless deviceand/or with other equipment in the wireless communication network thatenable and/or provide wireless access to the wireless device. As such,it can be any kind of network node which may comprise a radio networknode such as radio access node 420 (which can include a base station,radio base station, base transceiver station, base station controller,network controller, gNB, NR BS, evolved Node B (eNB), Node B,Multi-cell/multicast Coordination Entity (MCE), relay node, accesspoint, radio access point, Remote Radio Unit (RRU), Remote Radio Head(RRH), a multi-standard BS (also known as MSR BS), etc.), a core networknode (e.g., MME, SON node, a coordinating node, positioning node, MDTnode, etc.), or even an external node (e.g., 3rd party node, a nodeexternal to the current network), etc. The network node may alsocomprise a test equipment. For example, a network node may have multipleantennas.

The term “radio network node” used herein can be any kind of networknode comprised in a radio network which may further comprise any of basestation (BS), radio base station, base transceiver station (BTS), basestation controller (BSC), radio network controller (RNC), evolved Node B(eNB or eNodeB), Node B, multi-standard radio (MSR) radio node such asMSR BS, relay node, donor node controlling relay, radio access point(AP), transmission points, transmission nodes, Remote Radio Unit (RRU)Remote Radio Head (RRH), nodes in distributed antenna system (DAS) etc.

The term radio access technology (RAT) may refer to any RAT e.g. UTRA,E-UTRA, narrow band internet of things (NB-IoT), WiFi, Bluetooth, nextgeneration RAT (NR), 4G, 5G, etc. Any of the first and the second nodesmay be capable of supporting a single or multiple RATs.

The term “radio node” may be used to denote a UE (e.g., wireless device410) or a radio network node (e.g., radio access node 420). A radio nodemay also be in some cases interchangeably called a transmission point(TP) or transmission reception point (TRP).

The embodiments are applicable to single carrier as well as tomulticarrier or carrier aggregation (CA) operation of the UE in whichthe UE is able to receive and/or transmit data to more than one servingcells. The term carrier aggregation (CA) is also called (e.g.interchangeably called) “multi-carrier system”, “multi-cell operation”,“multi-carrier operation”, “multi-carrier” transmission and/orreception. In CA one of the component carriers (CCs) is the primarycomponent carrier (PCC) or simply primary carrier or even anchorcarrier. The remaining ones are called secondary component carrier (SCC)or simply secondary carriers or even supplementary carriers. The servingcell is interchangeably called as primary cell (PCell) or primaryserving cell (PSC). Similarly, the secondary serving cell isinterchangeably called as secondary cell (SCell) or secondary servingcell (SSC).

The term “radio signal” may also be interchangeably used with the termradio channel and may comprise physical or logical channel Examplesignals/channels: reference signal, synchronization signal, broadcastchannel, paging channel, control channel, data cannel, shared channel,etc.

In certain embodiments, radio access nodes 420 may interface with aradio network controller. The radio network controller may control radioaccess nodes 420 and may provide certain radio resource managementfunctions, mobility management functions, and/or other suitablefunctions. In certain embodiments, the functions of the radio networkcontroller may be included in radio access node 420. The radio networkcontroller may interface with a core network node 440. In certainembodiments, the radio network controller may interface with the corenetwork node 440 via an interconnecting network 430.

The interconnecting network 430 may refer to any interconnecting systemcapable of transmitting audio, video, signals, data, messages, or anycombination of the preceding. The interconnecting network 430 mayinclude all or a portion of a public switched telephone network (PSTN),a public or private data network, a local area network (LAN), ametropolitan area network (MAN), a wide area network (WAN), a local,regional, or global communication or computer network such as theInternet, a wireline or wireless network, an enterprise intranet, or anyother suitable communication link, including combinations thereof.

In some embodiments, the core network node 440 may manage theestablishment of communication sessions and various otherfunctionalities for wireless devices 410. Examples of core network node440 may include MSC, MME, SGW, PGW, O&M, OSS, SON, positioning node(e.g. E-SMLC), MDT node, etc. Wireless devices 410 may exchange certainsignals with the core network node using the non-access stratum layer.In non-access stratum signaling, signals between wireless devices 410and the core network node 440 may be transparently passed through theradio access network. In certain embodiments, radio access nodes 420 mayinterface with one or more network nodes over an internode interface.For example, radio access nodes 420 may interface over an X2 interfacewith each other.

Although FIG. 4 illustrates a particular arrangement of network 400, thepresent disclosure contemplates that the various embodiments describedherein may be applied to a variety of networks having any suitableconfiguration. For example, network 400 may include any suitable numberof wireless devices 410 and radio access nodes 420, as well as anyadditional elements suitable to support communication between wirelessdevices or between a wireless device and another communication device(such as a landline telephone). The embodiments may be implemented inany appropriate type of telecommunication system supporting any suitablecommunication standards and using any suitable components, and areapplicable to any radio access technology (RAT) or multi-RAT systems inwhich the wireless device receives and/or transmits signals (e.g.,data). While certain embodiments are described for NR and/or LTE, theembodiments are applicable to any RAT, such as UTRA, E-UTRA, narrow bandinternet of things (NB-IoT), WiFi, Bluetooth, next generation RAT (NR,NX), 4G, 5G, LTE FDD/TDD, WCDMA/HSPA, GSM/GERAN, WLAN, CDMA2000, etc.

It should be understood that an actual implementation of network 400 mayinclude multiple network nodes 420 and UEs 410, and may include elementsnot illustrated herein. Moreover, it should be understood that differentcommunication standards adopt somewhat different architectures and/oruse different nomenclature. Unless otherwise noted, then, the depictionof a particular network architecture, or the use of standards-relatednomenclature should not be construed as limiting communications controlas taught herein.

As mentioned above, the current DFT codebook is not adequate for MU-MIMOtransmissions. For a good MU-MIMO performance, the users that areco-scheduled with the same frequency resource should have good spatialseparation from each other. In addition, the precoding matrices shouldhave sidelobes as small as possible in order to reduce the co-channelinterference.

Embodiments of the present disclosure provide methods for codebookgeneration and selection for performing a MU-MIMO transmission. Forexample, the generation of the new codebook is based on a first codebook(e.g. DFT), using a reshaping matrix. The generated codebook has a oneto one mapping with the first codebook and has reduced sidelobe leakagecompared to the first codebook.

The First Codebook

One example of the first codebook can be an over-sampled DFT matrix. Fora generic one dimension (1D) antenna array with a number of antennaelements N and an over-sampling rate O (O=2, 4, . . . ), in total, therecan be B (B=NO) precoding matrices (beams). Then, the k-th precodingmatrix in the first codebook (w_(k) ⁽¹⁾∈B₁) is denoted by:

$\begin{matrix}{{w_{k}^{(1)} = {\frac{1}{\sqrt{N}}\left\lbrack {1,e^{\frac{j2\pi k}{B}},\ldots\mspace{14mu},e^{\frac{j2\pi nk}{B}},\ldots\mspace{14mu},e^{\frac{j2{\pi{({N - 1})}}k}{B}}} \right\rbrack}^{T}},{k = 0},1,\ldots\mspace{14mu},{B - 1}} & (1)\end{matrix}$

wherein B₁ corresponds to the first codebook.

Generating the Second Codebook

A generic way of generating the second codebook with reduced sidelobeleakage is to reshape the first codebook (e.g. DFT matrix above) byapplying a reshaping matrix to every precoding matrix of the firstcodebook, as follows:w _(k) ⁽²⁾ =R _(k) w _(k) ⁽¹⁾ ,k=0,1, . . . ,B−1  (2)

Where w_(k) ⁽²⁾∈B₂ refers to the k-th precoding matrix in thecorresponding second codebook; R_(k) is a reshaping matrix per precodingmatrix and B₂ corresponds to the second codebook.

Alternatively, if a single reshaping matrix is applied to all theprecoding matrices of the first codebook, the second codebook can begenerated and is denoted as follows:B ₂ =RB ₁  (3)

Where R is the reshaping matrix per codebook.

It can be seen, from equations (2) and (3), that the first and secondcodebooks have a one to one mapping. The selection of the reshapingmatrix should allow the precoding matrices in the second codebook tohave the same main lobe direction as the direction of the correspondingprecoding matrices in the first codebook. However, the main lobe width(e.g. 3 dB width) can be different between the precoding matrices fromthe first and second codebooks. The generated second codebook shouldhave sidelobe leakage lower than the sidelobe leakage of the firstcodebook.

Now, examples of different reshaping matrices will be described.

Sidelobe Nulling Reshaping

One exemplary method of generating the second codebook with reducedsidelobe leakage is to null or cancel the leakage/interference in thesidelobe directions of the regular DFT precoding matrices. For instance,in FIG. 3, the radiation pattern of a 8Tx DFT precoding matrix (at index0) shows that there are in total 6 sidelobes on the two sides of themain-lobe. Therefore, the direction of each sidelobe peak can bedetermined by looking at the radiation pattern as illustrated in FIG. 3.The directions corresponding to the sidelobe peaks or anypoints/positions close to the peaks can be selected as the nullingdirections of the new precoding matrices of the second codebook.

The corresponding new precoding matrix should have the same main-lobedirection as the precoding matrix of the first codebook. Also, the newprecoding matrix has reduced leakage in the selected sidelobe directionscompared to the precoding matrix of the first codebook. The new (orsecond) codebook can be thus generated by forming a nulling in thesidelobe directions using the zero-forcing principle. It should beappreciated by a person skilled in the art that other principles may beused as well to null the sidelobe directions.

For each DFT precoding matrix w_(k) ⁽¹⁾(k=0, 1, . . . , B−1) in firstcodebook, the corresponding new precoding matrix with reduced sidelobeleakage can be generated with the following steps.

First, determine the sidelobe directions of the DFT precoding matrixw_(k) ⁽¹⁾. For an over-sampled DFT codebook, the precoding matrixindexes k_(m) at the sidelobe directions can be determined by:k _(m)=(O*m+k+O/2)% B,m=1, . . . ,N−2  (4)

An example of k_(m) values with N=8, O=2 is given in Table 1.

TABLE 1 Sidelobe precoding matrix indexes k_(m) with N = 8, O = 2 k_(m)k m = 1 m = 2 m = 3 m = 4 m = 5 m = 6 0 3 5 7 9 11 13 1 4 6 8 10 12 14 25 7 9 11 13 15 3 6 8 10 12 14 0 4 7 9 11 13 15 1 5 8 10 12 14 0 2 6 9 1113 15 1 3 7 10 12 14 0 2 4 8 11 13 15 1 3 5 9 12 14 0 2 4 6 10 13 15 1 35 7 11 14 0 2 4 6 8 12 15 1 3 5 7 9 13 0 2 4 6 8 10 14 1 3 5 7 9 11 15 24 6 8 10 12

Second, select the sidelobe directions to be nulled. For example, thesedirections can correspond to the sidelobe peaks or points close to thesidelobe peaks. Then, form a channel matrix with the precoding matricescorresponding to the directions to be nulled. The channel matrix can beexpressed as:H _(k)=[W _(k) ₁ , . . . ,W _(k′) , . . . ,w _(k) _(m) ]*m∈[1,2, . . .,N−2]  (5)

where [ ]* denotes the conjugate of a matrix.

Third, calculate the nulling precoding weight with the zero-forcingprinciple as follows:w _(k) ⁽²⁾ ={I−H _(k)(H _(k) ^(H) H _(k))⁻¹ H _(k) ^(H) }w _(k) ⁽¹⁾  (6)

where, I is an identity matrix with size of N×N. It should be noted thatthe zero-forcing technique is just an example for nulling/cancelling theleakage. Other techniques can be used as will be appreciated by a personskilled in the art.

Finally, perform a power normalization and back-off with w_(k) ⁽²⁾ asthe following to normalize the total power per layer and secure themaximum power per antenna:w _(k) ⁽²⁾ =∝{I−H _(k)(H _(k) ^(H) H _(k))⁻¹ H _(k) ^(H) }W _(k) ⁽¹⁾

Thus, the new precoding matrix with reduced sidelobe leakage isgenerated. The final precoding matrix of the second codebook can beexpressed as:w _(k) ⁽²⁾ =R _(k) w _(k) ⁽¹⁾

Where R_(k)=∝{I−H_(k)(H_(k) ^(H)H_(k))⁻¹H_(k) ^(H)} is the reshapingmatrix, with ∝ being a factor for power normalization and back-off

Tapered Window Reshaping

Another method of generating the second codebook with reduced sidelobeleakage is to reshape the first codebook by applying a tapered window toevery precoding matrix in the first codebook, this can be expressed as:

$\begin{matrix}{{B_{2} = {RB_{1}}}{{Where},{R = \begin{bmatrix}{r(0)} & \ldots & 0 \\\vdots & {r(n)} & \vdots \\0 & \ldots & {r\left( {N - 1} \right)}\end{bmatrix}}}} & (7)\end{matrix}$and r(n) is the n-th coefficient of a tapered window generated, forinstance, with a Chebyshev window [3] or a Taylor window [4].

It should be noted that other methods for generating a tapered windowcan be considered by a person skilled in the art.

Generating the Two-Dimensional Second Codebook

The second codebook per dimension as described above can be used togenerate the two-dimensional (2D) second codebook in a way similar as inequation (1) for the 2D AAS. The 2D second codebook is given by:

$\begin{matrix}{W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(2)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(2)}}\end{bmatrix}} & (8)\end{matrix}$

Where w_(h) ⁽²⁾ and w_(v) ⁽²⁾ are the precoding matrices for thehorizontal and vertical directions selected from the second codebook,respectively.

The 2D second codebook can also be generated based on the first codebookand the second codebook in a mixed manner. For instance, the secondcodebook is used in the horizontal direction and the first codebook isused in the vertical direction as shown below:

$\begin{matrix}{W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(1)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(1)}}\end{bmatrix}} & (9)\end{matrix}$

Where w_(v) ⁽¹⁾ are the precoding matrices for the vertical directionand selected from the first codebook and w_(h) ⁽²⁾ are the precodingmatrices for the horizontal direction and selected from the secondcodebook.

It should be noted that a precoding matrix consists of one precodingvector or several precoding vectors. Also, the precoding matrices mayrefer to beamforming weights used by the network node (such as an gNB,eNB or base station) to transmit data to a wireless device.

It should be noted that the one-dimension codebook comprises precodingmatrices for a 1D antenna and the 2D codebook comprises precodingmatrices for a 2D antenna.

Radiation Patterns

FIGS. 5 and 6 show some radiation patterns of the second codebook,generated with sidelobe nulling based reshaping, referred to as thesidelobe leakage reduced (SLR) codebook, in comparison to the radiationpatterns of the first codebook, referred to as the DFT codebook.

More specifically, FIGS. 5 and 6 illustrate the radiation patterns of aSLR codebook for a linear antenna array with 8Tx and 16Tx and with allthe sidelobes selected (i.e. sidelobe interference nulled) forgenerating the SLR codebook. The radiation patterns of the SLR codebookare also shown in comparison with the radiation patterns of the regularDFT codebook. Also, the radiation patterns are plotted with theassumption that the channel is LOS, and the gain per antenna element isflat.

From FIGS. 5 and 6, it can be seen that the SLR codebook has much lowersidelobe leakage compared to the regular DFT codebook. The firstsidelobe leakage of the regular DFT codebook is about −12.8 dB, whichwould make it impossible for the UEs to reach a peak throughput per UE.With the SLR codebook, the sidelobe leakage is reduced to −24.8 dB,which is low enough for the UEs to achieve a per UE peak throughput with64QAM. Furthermore, the range of near-to-zero sidelobe interference iswide enough to cover the angle of spread of multi-path in NLOSscenarios. The overall sidelobe leakage can be further reduced with anincrease of antenna elements, which means that more gain can be achievedfor MU-MIMO transmissions by using the SLR codebook.

It can be also observed that with the SLR codebook and full sidelobeinterference nulling, there is about 3.7˜3.9 dB power back-off to ensurethat the maximum power per antenna element is not exceeded, in casethere is per antenna power limitation. Furthermore, the main-lobe isexpanded a little bit wider compared with the regular DFT codebook. Forinstance, in FIG. 6 with 16Tx, the −20 dB beam width is expanded from6.5° to 8.7°.

Adaptive Codebook Selection

As indicated above and illustrated in FIGS. 5 and 6, there can be seenthat about 3.7˜3.9 dB power is lost if the SLR codebook is used in aSU-MIMO transmission due to the applied power back-off. So, precodingwith the SLR codebook is not good for SU-MIMO transmissions. Whether aUE is scheduled for a SU-MIMO or MU-MIMO transmission is decided by theeNB/gNB per TTI scheduling, and can be dynamically changed. As such, anadaptive codebook selection at the eNB/gNB side is needed. For example,when the first codebook is used by the UE to select and report the PMI,the eNB/gNB uses the reported PMI to generate a precoding matrixbelonging to the second codebook. If the UE is scheduled for a SU-MIMOtransmission, the precoding matrix corresponding to the reported PMIfrom the first codebook is selected. If the UE is scheduled for aMU-MIMO transmission, the precoding matrix generated based on thereported PMI and belonging to the second codebook is selected.

With an adaptive codebook selection at the eNB/gNB side, higher MU-MIMOgain can be achieved without performance degradation for a SU-MIMOtransmission.

Now turning to FIG. 7, a signaling diagram between a UE and a networknode will be described. The UE can be one of the UEs 410, the networknode can be the network node 420 of FIG. 4. The communication betweenthe UE 410 and the network node 420 can be exchanged over thecommunication network 400, for example.

The UE 410 may be configured with a first codebook, i.e. the regular DFTcodebook, for example. The network node 420 may be configured with thefirst codebook (DFT codebook) and generates a second codebook (e.g., theSLR codebook) based on the first codebook, according to the embodimentsas described above.

The UE 410 may determine a precoding matrix indicator (PMI) or an indexin the first codebook. The precoding matrix indicator or the index maybe determined based on channel quality for a SU-MIMO transmission andother parameters, that are well-known to a person skilled in the art.

The UE 410 then sends the determined index or PMI (that includes theindex) to the network node 420, in a message (step 710). The message canbe a CSI report, for example.

The network node 420 may determine if a MU-MIMO transmission isscheduled or a SU-MIMO transmission is scheduled (step 720).

Upon determining that a MU-MIMO transmission is scheduled, the networknode 420 determines a precoding matrix from the second codebook based onthe received PMI (step 730). To do so, the network node 420 uses thereceived PMI or index to obtain the corresponding precoding matrix inthe second codebook, which was generated based one the first codebook,as described above. Alternatively, if the second codebook is notgenerated in advance, the network node can generate the precoding matrixfrom the second codebook based on the precoding matrix in the firstcodebook, that corresponds to the PMI. To do so, the network node canuse equations (4) to (7) for example.

Upon determining that a SU-MIMO transmission is scheduled, the networknode selects the precoding matrix corresponding to the PMI or index fromthe first codebook (step 740).

In step 750, the network node 420 can transmit data to the UE 410, usingthe determined precoding matrix (e.g. beamforming weights) based on thetype of transmission (SU-MIMO or MU-MIMO).

It should be noted that in an alternative embodiment, for example, in aTime Division Duplex (TDD) mode, the network node 420 can estimate aPMI, based on uplink reference signals, for example. In this case, itdoes not need to receive any PMI or index from the UE 410.

FIG. 8 illustrates a flow chart for a method 800 of performing MU-MIMOtransmissions in a communication network 400, for example. The methodcan be performed in a network node 420 which has multiple antennas or anAAS.

Method 800 includes:

Block 810: Obtaining a precoding matrix indicator (PMI) for a firstcodebook for use in a Single User Multiple Input Multiple Output(SU-MIMO) transmission;

Block 820: Determining a precoding matrix for a second codebook, basedon the obtained precoding matrix indicator; and

Block 830: Selecting the determined precoding matrix for the secondcodebook in response to determining that an User Equipment (UE) isscheduled for a Multi-User (MU)-MIMO transmission.

In some embodiments, the PMI can be obtained by receiving a report or amessage from the wireless device. The report can be a CSI-RS report,which includes a PMI, for example. In other embodiments, the PMI can beestimated by the network node 420, based on uplink reference signals,for example.

In some embodiments, the method 800 may further comprise selecting aprecoding matrix, corresponding to the obtained PMI, from the firstcodebook in response to determining that the UE is scheduled for aSU-MIMO transmission.

In some embodiments, the precoding matrix for the second codebook may bedetermined by applying a reshaping matrix to a precoding matrix thatcorresponds to the obtained PMI in the first codebook.

More generally, in some embodiments, the second codebook may begenerated based on the first codebook by using a reshaping matrix.

In some embodiments, the reshaping matrix may be designed to suppresssidelobe leakage in peak directions of sidelobes of precoding matricesof the first codebook.

For example, the reshaping matrix may comprise a matrix formed withprecoding matrices from the first codebook, to which nulling precodingweights are applied, so that sidelobe leakage in the peak directions ofthe sidelobes of the precoding matrices are nulled.

In other examples, the reshaping matrix may comprise a matrix formed byapplying a tapered window to the first codebook. In some embodiments,the tapered window can be generated using a Chebyshev window or a Taylorwindow.

In some embodiments, the second codebook can have a one to one mappingwith the first codebook.

In some embodiments, the second codebook can have a lower sidelobeleakage compared to sidelobe leakage of the first codebook in theselected sidelobe directions.

In some embodiments, method 800 further comprises generating atwo-dimension (2D) codebook based on the second codebook.

For example, the 2D codebook can comprise precoding matrices for ahorizontal direction selected from the second codebook and precodingmatrices for a vertical direction selected from the second codebook. The2D codebook, denoted as W₁ ⁽²⁾ can be given by:

$W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(2)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(2)}}\end{bmatrix}$where w_(h) ⁽²⁾ are the precoding matrices for the horizontal directionselected from the second codebook and w_(v) ⁽²⁾ are the precodingmatrices for the vertical direction selected from the second codebookand ⊗ is a Kronecker product.

In some embodiments, the two-dimension (2D) codebook can be generatedbased on the second codebook and the first codebook.

For example, the 2D codebook can comprise precoding matrices for ahorizontal direction selected from the second codebook and precodingmatrices for a vertical direction selected from the first codebook.

Then, the 2D codebook, denoted as W₁ ⁽²⁾ can be given by:

$W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(1)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(1)}}\end{bmatrix}$where w_(h) ⁽²⁾ are the precoding matrices for the horizontal directionselected from the second codebook and w_(v) ⁽¹⁾ are the precodingmatrices for the vertical direction selected from the first codebook and⊗ is a Kronecker product.

In other examples, the 2D codebook can comprise precoding matrices for ahorizontal direction selected from the first codebook and precodingmatrices for a vertical direction selected from the second codebook.

Then, the 2D codebook, denoted as W₁ ⁽²⁾ can be given by:

$W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(1)} \otimes w_{v}^{(2)}} & 0 \\0 & {w_{h}^{(1)} \otimes w_{v}^{(2)}}\end{bmatrix}$where w_(h) ⁽¹⁾ are the precoding matrices for the horizontal directionselected from the first codebook and w_(v) ⁽²⁾ are the precodingmatrices for the vertical direction selected from the second codebook.

It is understood that in some embodiments, the blocks of the flowchartsabove may occur out of the order as shown in the figures. For example,two blocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved.

Also, it should be noted that the generated second codebook can be madeavailable to the wireless device or UE 410. In this case, when the UEdetermines an index/PMI to report to the network node, it can determinean index/PMI from the second codebook. In the network node side, if thenetwork node 420 determines that a SU-MIMO transmission is scheduled,then the network node 420 can use the received index/PMI to get thecorresponding beamforming weights from the first codebook. If thenetwork node 420 determines that a MU-MIMO transmission is scheduled,then, it can use the received index/PMI to get the correspondingbeamforming weights (precoding matrix) from the second codebook.

Some embodiments of a wireless device 410 will now be described withrespect to FIG. 9. Even though the expression wireless device is usedthroughout the description, it is to be understood that the expressionis used generically. In that sense, a wireless device (WD) generallyrefers to a device capable, configured, arranged and/or operable tocommunicate wirelessly with one or more network nodes (e.g., radionetwork nodes) and/or with one or more other wireless devices.

FIG. 9 is a block diagram of an exemplary wireless device 410 inaccordance with some embodiments. The wireless device 410 includes anantenna 920, radio front-end circuitry 930, processing circuitry 910, acomputer-readable storage medium 940, an input interface 960 and outputinterface 970. Antenna 920 may include multiple antennas or antennaarrays, and is configured to send and/or receive wireless signals, andis connected to radio front-end circuitry 930. The radio front-endcircuitry 930 may comprise various filters and amplifiers, is connectedto antenna 920 and processing circuitry 910, and is configured tocondition signals communicated between antenna 920 and processingcircuitry 910. In certain alternative embodiments, UE 410 may notinclude radio front-end circuitry 930, and processing circuitry 910 mayinstead be connected to antenna 920 without radio front-end circuitry930.

In some embodiments, the processing circuitry 910 may comprise aprocessor 980 and a memory such as the storage/memory 940, the processor980 being connected to the input and output interfaces 960 and 970. Thememory 940 contains instructions which, when executed by the processor,configure the processor to perform one or more functions describedherein.

Processing circuitry 910 may comprise and/or be connected to and/or beadapted for accessing (e.g., writing to and/or reading from) memory 940.Such memory 940 may be configured to store code executable by controlcircuitry and/or other data, e.g., data pertaining to communication,e.g., configuration and/or address data of nodes, etc. Processingcircuitry 910 may be configured to control any of the methods describedherein and/or to cause such methods to be performed, e.g., by theprocessor. Corresponding instructions may be stored in the memory 940,which may be readable and/or readably connected to the processingcircuitry 910.

Antenna 920, radio front-end circuitry 930, processing circuitry 910,and/or input interface 960 and output interface 970 may be configured toperform any transmitting operations described herein as being performedby a wireless device. Any information, data and/or signals may betransmitted to a network node and/or another wireless device. The inputinterface 960 and output interface 970 can be collectively referred toas a network interface, which is connected to the processor and/ormemory.

Other embodiments of wireless device 410 may include additionalcomponents beyond those shown in FIG. 9 that may be responsible forproviding certain aspects of the UE's functionalities, including any ofthe functionalities described above and/or any additionalfunctionalities (including any functionality necessary to support thesolution described above). As just one example, wireless device 410 mayinclude input devices and circuits, output devices, and one or moresynchronization units or circuits, which may be part of the processor.Input devices include mechanisms for entry of data into wireless device410. For example, input devices may include input mechanisms, such as amicrophone, input elements, a display, etc. Output devices may includemechanisms for outputting data in audio, video and/or hard copy format.For example, output devices may include a speaker, a display, etc.

Embodiments of a network node 420 will now be described with respect toFIGS. 10 and 11.

FIG. 10 is a block diagram of a network node 420, such as a basestation, an eNodeB or a gNB, configured to perform a MU-MIMOtransmission according to some embodiments. The network node 420 hasprocessing circuitry 1010 having a memory 1050 and a processor 1040. Thenetwork node 420 further comprises a network interface 1030 and one ormore transceivers 1020. The transceivers may comprise multiple antennasor AAS. In some embodiments, the transceiver 1020 facilitatestransmitting wireless signals to and receiving wireless signals fromwireless device 410 (e.g., via an antenna), the one or more processors1040 executes instructions to provide some or all of the functionalitiesdescribed above (such as method 800) as being provided by the networknode 420, the memory 1050 stores the instructions for execution by theone or more processors 1040, and the network interface 1030 communicatessignals to backend network components, such as a gateway, switch,router, Internet, Public Switched Telephone Network (PSTN), core networknodes or radio network controllers, etc. The network interface 1030 isconnected to the processor and/or memory.

As an example, the processor 1040 is configured to perform method 800.The one or more processors 1040 may include any suitable combination ofhardware and software implemented in one or more modules to executeinstructions and manipulate data to perform some or all of the describedfunctions of the network node 420, such as method 800. In someembodiments, the one or more processors 1040 may include, for example,one or more computers, one or more central processing units (CPUs), oneor more microprocessors, one or more applications, one or moreapplication specific integrated circuits (ASICs), one or more fieldprogrammable gate arrays (FPGAs) and/or other logic. In certainembodiments, the one or more processors 1040 may comprise one or more ofthe modules discussed below with respect to FIG. 11.

The memory 1050 is generally operable to store instructions, such as acomputer program, software, an application including one or more oflogic, rules, algorithms, code, tables, etc. and/or other instructionscapable of being executed by one or more processors 1040. Examples ofmemory 1050 include computer memory (for example, Random Access Memory(RAM) or Read Only Memory (ROM)), mass storage media (for example, ahard disk), removable storage media (for example, a Compact Disk (CD) ora Digital Video Disk (DVD)), and/or or any other volatile ornon-volatile, non-transitory computer-readable and/orcomputer-executable memory devices that store information.

Other embodiments of radio network node 420 may include additionalcomponents beyond those shown in FIG. 10 that may be responsible forproviding certain aspects of the radio network node's functionalities,including any of the functionalities described above and/or anyadditional functionalities (including any functionality necessary tosupport the solutions described above). The various different types ofnetwork nodes may include components having the same physical hardwarebut configured (e.g., via programming) to support different radio accesstechnologies, or may represent partly or entirely different physicalcomponents.

Processors, interfaces, and memory similar to those described withrespect to FIG. 10 may be included in other network nodes (such as corenetwork node 430). Other network nodes may optionally include or notinclude a wireless interface (such as the transceiver described in FIG.10).

In some embodiments, the network node 420 may comprise a series ofmodules configured to implement the functionalities of the network node420 described above. Referring to FIG. 11, in some embodiments, thenetwork node 420 may comprise an obtaining module 1110, a determiningmodule 1120 and a selecting module 1130. The obtaining module 1110 isconfigured to obtain a precoding matrix indicator (PMI) for a firstcodebook for use in a Single User Multiple Input Multiple Output(SU-MIMO) transmission. The determining module 1120 is configured to,determine a precoding matrix for a second codebook, based on theobtained precoding matrix indicator. The selecting module 1130 isconfigured to select the determined precoding matrix for the secondcodebook in response to determining that an User Equipment (UE) isscheduled for a Multi-User (MU)-MIMO transmission.

The network node 420 may further comprise a generating module forgenerating the second codebook based on the first codebook.

It will be appreciated that the various modules may be implemented ascombination of hardware and/or software, for instance, the processor,memory and transceiver(s) of a network node 420 shown in FIG. 10. Someembodiments may also include additional modules to support additionaland/or optional functionalities.

Embodiments may also be practiced in distributed computing environmentswhere tasks are performed by remote-processing devices that are linkedthrough a communications network.

FIG. 12 is a schematic block diagram illustrating a virtualizationenvironment 1200 in which functions implemented by some embodiments maybe virtualized. In the present context, virtualizing means creatingvirtual versions of apparatuses or devices which may includevirtualizing hardware platforms, storage devices and networkingresources. As used herein, virtualization can be applied to a networknode 420 (e.g., a virtualized base station or a virtualized radio accessnode) or to a device 410 (e.g., a UE, a wireless device or any othertype of communication device) or components thereof and relates to animplementation in which at least a portion of the functionality isimplemented as one or more virtual components (e.g., via one or moreapplications, components, functions, virtual machines or containersexecuting on one or more physical processing nodes in one or morenetworks).

In some embodiments, some or all of the functions described herein, suchas method 800, may be implemented as virtual components executed by oneor more virtual machines implemented in one or more virtual environments1200 hosted by one or more of hardware nodes 1230. Further, inembodiments in which the virtual node is not a radio access node or doesnot require radio connectivity (e.g., a core network node), then thenetwork node may be entirely virtualized.

The functions may be implemented by one or more applications 1220 (whichmay alternatively be called software instances, virtual appliances,network functions, virtual nodes, virtual network functions, etc.)operative to implement some of the features, functions, and/or benefitsof some of the embodiments disclosed herein. Applications 1220 are runin virtualization environment 1200 which provides hardware 1230comprising processing circuitry 1260 and memory 1290. Memory 1290contains instructions 1295 executable by processing circuitry 1260whereby application 1220 is operative to provide one or more of thefeatures, benefits, and/or functions disclosed herein.

Virtualization environment 1200, comprises general-purpose orspecial-purpose network hardware devices 1230 comprising a set of one ormore processors or processing circuitry 1260, which may be commercialoff-the-shelf (COTS) processors, dedicated Application SpecificIntegrated Circuits (ASICs), or any other type of processing circuitryincluding digital or analog hardware components or special purposeprocessors. Each hardware device may comprise memory 1290-1 which may benon-persistent memory for temporarily storing instructions 1295 orsoftware executed by processing circuitry 1260. Each hardware device maycomprise one or more network interface controllers (NICs) 1270, alsoknown as network interface cards, which include physical networkinterface 1280. Each hardware device may also include non-transitory,persistent, machine-readable storage media 1290-2 having stored thereinsoftware 1295 and/or instructions executable by processing circuitry1260. Software 1295 may include any type of software including softwarefor instantiating one or more virtualization layers 1250 (also referredto as hypervisors), software to execute virtual machines 1240 as well assoftware allowing it to execute functions, features and/or benefitsdescribed in relation with some embodiments described herein.

Virtual machines 1240, comprise virtual processing, virtual memory,virtual networking or interface and virtual storage, and may be run by acorresponding virtualization layer 1250 or hypervisor. Differentembodiments of the instance of virtual appliance 1220 may be implementedon one or more of virtual machines 1240, and the implementations may bemade in different ways.

During operation, processing circuitry 1260 executes software 1295 toinstantiate the hypervisor or virtualization layer 1250, which maysometimes be referred to as a virtual machine monitor (VMM).Virtualization layer 1250 may present a virtual operating platform thatappears like networking hardware to virtual machine 1240.

As shown in FIG. 12, hardware 1230 may be a standalone network node withgeneric or specific components. Hardware 1230 may comprise antenna 12225and may implement some functions via virtualization. Alternatively,hardware 1230 may be part of a larger cluster of hardware (e.g. such asin a data center or customer premise equipment (CPE)) where manyhardware nodes work together and are managed via management andorchestration (MANO) 12100, which, among others, oversees lifecyclemanagement of applications 1220.

Virtualization of the hardware is in some contexts referred to asnetwork function virtualization (NFV). NFV may be used to consolidatemany network equipment types onto industry standard high volume serverhardware, physical switches, and physical storage, which can be locatedin data centers, and customer premise equipment.

In the context of NFV, virtual machine 1240 may be a softwareimplementation of a physical machine that runs programs as if they wereexecuting on a physical, non-virtualized machine. Each of virtualmachines 1240, and that part of hardware 1230 that executes that virtualmachine, be it hardware dedicated to that virtual machine and/orhardware shared by that virtual machine with others of the virtualmachines 1240, forms a separate virtual network elements (VNE).

Still in the context of NFV, Virtual Network Function (VNF) isresponsible for handling specific network functions that run in one ormore virtual machines 1240 on top of hardware networking infrastructure1230 and corresponds to application 1220 in FIG. 12.

In some embodiments, one or more radio units 12200 that each include oneor more transmitters 12220 and one or more receivers 12210 may becoupled to one or more antennas 12225. Radio units 12200 may communicatedirectly with hardware nodes 1230 via one or more appropriate networkinterfaces and may be used in combination with the virtual components toprovide a virtual node with radio capabilities, such as a radio accessnode or a base station.

In some embodiments, some signalling can be effected with the use ofcontrol system 12230 which may alternatively be used for communicationbetween the hardware nodes 1230 and radio units 12200.

In this example, functions and method 800 of the network node 420described herein are implemented at the one or more processors 1040 canbe distributed across virtualization environment 1200 in any desiredmanner. In some particular embodiments, some or all of the functions andmethod 800 of the network node 420 described herein are implemented asvirtual components executed by one or more virtual machines 1240.

In some embodiments, a computer program including instructions which,when executed by at least one processor, causes the at least oneprocessor to carry out the functionality of a network node 420implementing one or more of the functions or method 800 of the networknode in a virtual environment according to any of the embodimentsdescribed herein is provided. In some embodiments, a carrier comprisingthe aforementioned computer program product is provided. The carrier isone of an electronic signal, an optical signal, a radio signal, or acomputer readable storage medium (e.g., a non-transitory computerreadable medium such as memory).

Some embodiments may be represented as a non-transitory software productstored in a machine-readable medium (also referred to as acomputer-readable medium, a processor-readable medium, or a computerusable medium having a computer readable program code embodied therein).The machine-readable medium may be any suitable tangible mediumincluding a magnetic, optical, or electrical storage medium including adiskette, compact disk read only memory (CD-ROM), digital versatile discread only memory (DVD-ROM) memory device (volatile or non-volatile), orsimilar storage mechanism. The machine-readable medium may containvarious sets of instructions, code sequences, configuration information,or other data, which, when executed, cause a processor to perform stepsin a method according to one or more of the described embodiments. Thoseof ordinary skill in the art will appreciate that other instructions andoperations necessary to implement the described embodiments may also bestored on the machine-readable medium. Software running from themachine-readable medium may interface with circuitry to perform thedescribed tasks.

The above-described embodiments are intended to be examples only.Alterations, modifications and variations may be effected to theparticular embodiments by those of skill in the art without departingfrom the scope of the description, which is defined solely by theappended claims.

ABBREVIATIONS

The present description may comprise one or more of the followingabbreviation:

AAS Active Antenna System

CSI-RS Channel State Information Reference Signal

DFT Discrete Fourier Transform

DMRS Demodulation Reference Signal

FD-MIMO Full Dimension MIMO

GoB Grid-of-beams

PMI Precoding Matrix Indicator

SRS Sounding Reference Signal

1×RTT CDMA2000 1×Radio Transmission Technology

3GPP 3rd Generation Partnership Project

5G 5th Generation

ABS Almost Blank Subframe

ARQ Automatic Repeat Request

BCCH Broadcast Control Channel

BCH Broadcast Channel

CA Carrier Aggregation

CC CSI Channel State Information

DCCH Dedicated Control Channel

DL Downlink

DM Demodulation

DMRS Demodulation Reference Signal

DRX Discontinuous Reception

DTX Discontinuous Transmission

DTCH Dedicated Traffic Channel

DUT Device Under Test

ECGI Evolved CGI

eNB E-UTRAN NodeB

ePDCCH enhanced Physical Downlink Control Channel

E-UTRA Evolved UTRA

E-UTRAN Evolved UTRAN

FDD Frequency Division Duplex

GERAN GSM EDGE Radio Access Network

gNB Base station in NR (corresponding to eNB in LTE)

GSM Global System for Mobile communication

HARQ Hybrid Automatic Repeat Request

HO Handover

HSPA High Speed Packet Access

HRPD High Rate Packet Data

LOS Line of Sight

LPP LTE Positioning Protocol

LTE Long-Term Evolution

MAC Medium Access Control

MME Mobility Management Entity

MSC Mobile Switching Center

NPDCCH Narrowband Physical Downlink Control Channel

NR New Radio

OFDMA Orthogonal Frequency Division Multiple Access

OSS Operations Support System

PBCH Physical Broadcast Channel

P-CCPCH Primary Common Control Physical Channel

PCell Primary Cell

PDCCH Physical Downlink Control Channel

PDSCH Physical Downlink Shared Channel

PGW Packet Gateway

PLMN Public Land Mobile Network

PMI Precoder Matrix Indicator

PRACH Physical Random Access Channel

PRS Positioning Reference Signal

PSS Primary Synchronization Signal

PUCCH Physical Uplink Control Channel

PUSCH Physical Uplink Shared Channel

ACH Random Access Channel

QAM Quadrature Amplitude Modulation

RAN Radio Access Network

RAT Radio Access Technology

RLM Radio Link Management

RNC Radio Network Controller

RNTI Radio Network Temporary Identifier

RRC Radio Resource Control

RRM Radio Resource Management

RS Reference Signal

RSCP Received Signal Code Power

RSRP Reference Symbol Received Power OR

Reference Signal Received Power

RSRQ Reference Signal Received Quality OR

Reference Symbol Received Quality

RSSI Received Signal Strength Indicator

RSTD Reference Signal Time Difference

SCH Synchronization Channel

SCell Secondary Cell

SIB System Information Block

SNR Signal to Noise Ratio

TDD Time Division Duplex

TDOA Time Difference of Arrival

TOA Time of Arrival

TTI Transmission Time Interval

UE User Equipment

UL Uplink

UMTS Universal Mobile Telecommunication System

USIM Universal Subscriber Identity Module

UTDOA Uplink Time Difference of Arrival

UTRA Universal Terrestrial Radio Access

UTRAN Universal Terrestrial Radio Access Network

WCDMA Wide CDMA

WLANWide Local Area Network

REFERENCES

The following reference(s) may be related to the present description:

-   [1] Qualcomm, Two-Dimensional Discrete Fourier Transform (2D-DFT)    based codebook for elevation beamforming, PCT/CN2013/007164-   [2] 3GPP TS 36.213 V14.2.0-   [3] https://www.mathworks.com/help/signal/ref/chebwin.html-   [4] https://www.mathworks.com/help/signal/ref/taylorwin.html

What is claimed is:
 1. A method in a network node, the methodcomprising: obtaining a precoding matrix indicator (PMI) for a firstcodebook for use in a Single User Multiple Input Multiple Output(SU-MIMO) transmission; determining a precoding matrix for a secondcodebook, based on the obtained precoding matrix indicator, whereindetermining the precoding matrix for the second codebook comprisesapplying a reshaping matrix to a precoding matrix that corresponds tothe obtained PMI in the first codebook; and selecting the determinedprecoding matrix for the second codebook in response to determining thatan User Equipment (UE) is scheduled for a Multi-User (MU)-MIMOtransmission.
 2. A network node, comprising a network interface and aprocessing circuitry connected thereto, the processing circuitrycomprising a processor and a memory connected thereto, the memorycontaining instructions that, when executed, cause the processor to:obtain a precoding matrix indicator (PMI) for a first codebook for usein a Single User Multiple Input Multiple Output (SU-MIMO) transmission;determine a precoding matrix for a second codebook, based on theobtained precoding matrix indicator, wherein determining the precodingmatrix for the second codebook comprises applying a reshaping matrix toa precoding matrix that corresponds to the obtained PMI in the firstcodebook; and select the determined precoding matrix for the secondcodebook in response to determining that an User Equipment (UE) isscheduled for a Multi-User (MU)-MIMO transmission.
 3. The network nodeof claim 2, wherein the processor is configured to select a precodingmatrix, corresponding to the obtained PMI, from the first codebook inresponse to determining that the UE is scheduled for a SU-MIMOtransmission.
 4. The network node of claim 2, wherein the processor isconfigured to generate the second codebook based on the first codebookby using the reshaping matrix.
 5. The network node of claim 2, whereinthe processor is configured to form the reshaping matrix with precodingmatrices from the first codebook, to which nulling precoding weights areapplied, so that sidelobe leakage in peak directions of sidelobes of theprecoding matrices from the first codebook are nulled.
 6. The networknode of any of claim 2, wherein the processor is configured to form thereshaping matrix by applying a tapered window to the first codebook. 7.The network node of claim 6, wherein the processor is configured togenerate the tapered window using one of a Chebyshev window and Taylorwindow.
 8. The network node of claim 2, wherein the second codebook hasa one to one mapping with the first codebook.
 9. The network node ofclaim 2, wherein the second codebook has a lower sidelobe leakagecompared to sidelobe leakage of the first codebook in selected sidelobedirections.
 10. The network node of claim 2, wherein the processor isconfigured to generate a two-dimension (2D) codebook based on the secondcodebook.
 11. The network node of claim 10, wherein the 2D codebookcomprises precoding matrices for a horizontal direction selected fromthe second codebook and precoding matrices for a vertical directionselected from the second codebook.
 12. The network node of claim 11,wherein the 2D codebook, denoted as W₁ ⁽²⁾ is given by:$W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(2)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(2)}}\end{bmatrix}$ where w_(h) ⁽²⁾ are the precoding matrices for thehorizontal direction selected from the second codebook and w_(v) ⁽²⁾ arethe precoding matrices for the vertical direction selected from thesecond codebook and ⊗ is a Kronecker product.
 13. The network node ofclaim 2, wherein the processor is configured to generate a two-dimension(2D) codebook based on the second codebook and the first codebook. 14.The network node of claim 13, wherein the 2D codebook comprisesprecoding matrices for a horizontal direction selected from the secondcodebook and precoding matrices for a vertical direction selected fromthe first codebook.
 15. The network node of claim 14, wherein the 2Dcodebook, denoted as W₁ ⁽²⁾ is given by: $W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(2)} \otimes w_{v}^{(1)}} & 0 \\0 & {w_{h}^{(2)} \otimes w_{v}^{(1)}}\end{bmatrix}$ where w_(h) ⁽²⁾ are the precoding matrices for thehorizontal direction selected from the second codebook and w_(v) ⁽¹⁾ arethe precoding matrices for the vertical direction selected from thefirst codebook and ⊗ is a Kronecker product.
 16. The network node ofclaim 13, wherein the 2D codebook comprises precoding matrices for ahorizontal direction selected from the first codebook and precodingmatrices for a vertical direction selected from the second codebook. 17.The network node of claim 16, wherein the 2D codebook, denoted as W₁ ⁽²⁾is given by: $W_{1}^{(2)} = \begin{bmatrix}{w_{h}^{(1)} \otimes w_{v}^{(2)}} & 0 \\0 & {w_{h}^{(1)} \otimes w_{v}^{(2)}}\end{bmatrix}$ where w_(h) ⁽²⁾ are the precoding matrices for thehorizontal direction selected from the first codebook and w_(v) ⁽²⁾ arethe precoding matrices for the vertical direction selected from thesecond codebook.
 18. The network node of claim 2, wherein the processoris configured to receive from a wireless device a report comprising theprecoding matrix indicator.
 19. The network node of claim 2, wherein theprocessor is configured to estimate the PMI based on uplink referencesignals.